AIMC Topic: Sensitivity and Specificity

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Predicting outcome in clinically isolated syndrome using machine learning.

NeuroImage. Clinical Dec 4, 2014
We aim to determine if machine learning techniques, such as support vector machines (SVMs), can predict the occurrence of a second clinical attack, which leads to the diagnosis of clinically-definite Multiple Sclerosis (CDMS) in patients with a clini...
Image Interpretation, Computer-Assisted Adult Humans Demyelinating Diseases Disease Progression Sensitivity and Specificity Retrospective Studies Male Support Vector Machine Female Middle Aged Magnetic Resonance Imaging Young Adult Multiple Sclerosis
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An SSVEP-Based Brain-Computer Interface for Text Spelling With Adaptive Queries That Maximize Information Gain Rates.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Dec 2, 2014
This paper presents a brain-computer interface for text entry using steady-state visually evoked potentials (SSVEP). Like other SSVEP-based spellers, ours identifies the desired input character by posing questions (or queries) to users through a visu...
Brain-Computer Interfaces Evoked Potentials, Visual Communication Devices for People with Disabilities Word Processing Natural Language Processing Electroencephalography Information Storage and Retrieval Pattern Recognition, Automated Humans Machine Learning Female Reproducibility of Results Young Adult Sensitivity and Specificity Male Adolescent Child
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Ultrasound texture-based CAD system for detecting neuromuscular diseases.

International journal of computer assisted radiology and surgery Dec 2, 2014
PURPOSE: Diagnosis of neuromuscular diseases in ultrasonography is a challenging task since experts are often unable to discriminate between healthy and pathological cases. A computer-aided diagnosis (CAD) system for skeletal muscle ultrasonography w...
Humans Adult Sensitivity and Specificity Middle Aged Diagnosis, Computer-Assisted Ultrasonography Algorithms Reproducibility of Results Aged Aged, 80 and over Automation Neuromuscular Diseases Support Vector Machine Muscle, Skeletal Principal Component Analysis Myositis
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The Impact of Oversampling with SMOTE on the Performance of 3 Classifiers in Prediction of Type 2 Diabetes.

Medical decision making : an international journal of the Society for Medical Decision Making Dec 1, 2014
OBJECTIVE: To evaluate the impact of the synthetic minority oversampling technique (SMOTE) on the performance of probabilistic neural network (PNN), naïve Bayes (NB), and decision tree (DT) classifiers for predicting diabetes in a prospective cohort ...
Female Risk Factors Adult Sensitivity and Specificity Male Humans Neural Networks, Computer Algorithms Decision Trees Prospective Studies Middle Aged Bayes Theorem Diabetes Mellitus, Type 2 Selection Bias Models, Theoretical Iran Socioeconomic Factors Minority Groups
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Moving Away From Error-Related Potentials to Achieve Spelling Correction in P300 Spellers.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Nov 25, 2014
P300 spellers can provide a means of communication for individuals with severe neuromuscular limitations. However, its use as an effective communication tool is reliant on high P300 classification accuracies ( > 70%) to account for error revisions. E...
Reproducibility of Results Sensitivity and Specificity Natural Language Processing Bayes Theorem Pattern Recognition, Automated Brain-Computer Interfaces Event-Related Potentials, P300 Humans Communication Devices for People with Disabilities Machine Learning Word Processing Algorithms
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Robotic systems for percutaneous needle-guided interventions.

Minimally invasive therapy & allied technologies : MITAT : official journal of the Society for Minimally Invasive Therapy Nov 25, 2014
Several groups have developed robotic systems for invasive medical procedures. In this article we will focus on selected robotic systems for percutaneous needle-guided interventions using CT or MR imaging. We present six interventional robotic system...
Humans Radiography, Interventional Sensitivity and Specificity Image-Guided Biopsy Animals Biopsy, Needle Robotics Phantoms, Imaging Equipment Design Equipment Safety
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Computer-aided diagnosis from weak supervision: a benchmarking study.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Nov 20, 2014
Supervised machine learning is a powerful tool frequently used in computer-aided diagnosis (CAD) applications. The bottleneck of this technique is its demand for fine grained expert annotations, which are tedious for medical image analysis applicatio...
Microscopy Image Interpretation, Computer-Assisted Pattern Recognition, Automated Image Enhancement Sensitivity and Specificity Neoplasms Benchmarking Supervised Machine Learning Humans Diabetic Retinopathy Algorithms Reproducibility of Results
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Selective invocation of shape priors for deformable segmentation and morphologic classification of prostate cancer tissue microarrays.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Nov 12, 2014
Shape based active contours have emerged as a natural solution to overlap resolution. However, most of these shape-based methods are computationally expensive. There are instances in an image where no overlapping objects are present and applying thes...
Microscopy Image Interpretation, Computer-Assisted Pattern Recognition, Automated Image Enhancement Oligonucleotide Array Sequence Analysis Subtraction Technique Cell Nucleus Shape Sensitivity and Specificity Male Prostatic Neoplasms Neoplasm Grading Humans Machine Learning Algorithms Reproducibility of Results
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Quantifying the determinants of outbreak detection performance through simulation and machine learning.

Journal of biomedical informatics Nov 6, 2014
OBJECTIVE: To develop a probabilistic model for discovering and quantifying determinants of outbreak detection and to use the model to predict detection performance for new outbreaks.
Computational Biology Bayes Theorem Probability Humans Computer Simulation False Positive Reactions Machine Learning Sensitivity and Specificity Algorithms Disease Outbreaks ROC Curve
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Artificial neural network and falls in community-dwellers: a new approach to identify the risk of recurrent falling?

Journal of the American Medical Directors Association Oct 29, 2014
BACKGROUND: Identification of the risk of recurrent falls is complex in older adults. The aim of this study was to examine the efficiency of 3 artificial neural networks (ANNs: multilayer perceptron [MLP], modified MLP, and neuroevolution of augmenti...
Humans Neural Networks, Computer Age Factors Geriatric Assessment Sex Factors Recurrence Cross-Sectional Studies Independent Living Male Risk Assessment Accidental Falls Incidence Female Aged Aged, 80 and over Sensitivity and Specificity
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